SlideShare ist ein Scribd-Unternehmen logo
1 von 24
Downloaden Sie, um offline zu lesen
Combating Revenue Leakage
                       Prepared by




             With the Assistance of
                    Chris Paterson
                       JP Ducasse
Webinar Outline




Leakage – definition and overview
Overview of a general framework to combat leakage
   Measuring leakage
   Establishing mitigation policies
   Combating leakage
What you should consider




                                                    2
Combating revenue leakage
                                    Definition*

    Combating revenue leakage consists of
    engaging in activities that help a Post:
         Collect all the postage revenue owed to it, and
         Curb the sources/reasons of leakage.

    Leakage stems from one of four main risks
         Counterfeit (e.g., illegal issues, fake imprints)
         Bypass mail (e.g., mail inducted without any form
         of payment)
         Shortpaid or underpaid (e.g., mail tendered with
         insufficient postage)
         Problems related to billing or postage collection
         (e.g., bad cheques; accounting errors)

    Combating revenue leakage consists of setting
    policies to mitigate the sources of risks
* Source: UPU Consultative Committee – Postal Revenue Protection Working Group

                                                                                 3
Recent trends


Steps in the right direction          But room for improvement
 • Global awareness of leakage        • Not all posts have established a well-
 issues has increased (75% of posts   structured revenue protection function
 admit they experience leakage)



 • Posts have heavily invested in     • Mail acceptance and verification is still
 revenue protection technology,       very much manual and time consuming,
 making some channels more            and often plagued with inconsistencies in
 secure (meters, stamps)              performance.


 • Verification technologies (e.g.,   • Fraudsters too leverage technologies...
 OCR-based) becoming more             • New products may not be ‘leakage-free’
 effective and/or more affordable     • ROI of technology solutions is still an
 and scalable                         issue, e.g., for smaller posts



                                                                                    4
A broader choice of technologies is
               now available to fight leakage

           Evidencing
           • Deployment of digital meters in smaller emerging markets
           • Anti-fraud security measures (special inks, holograms…) for stamps
           Acceptance/verification
           • E-documentation
           • Sorters/counting machines for piece count (for sampling, verification
             or terminal dues purposes)
           • Modular dimensions/weight/data capture solutions for use in post
             offices
A few
examples   Processing
           • Lower-end sorters suitable for mid-tier posts
           • Large CFC with on the fly weighing of parcels or letters
           • Capability to trace back an item to a specific sender


           Billing/reconciling software solutions
           (e.g., USPS Permit RP project)


                                                                                     5
Two main challenges



Measuring and identification is difficult
   A touchy issue : leakages relate to posts’ weaknesses - a mix of fraud
   and (operational or accounting) issues;
   Amounts recovered are just the tip of the iceberg;
   Posts use multiple channels and processes;
   Data sources are diverse (spot checks, sampling, data from operations
   and from accounting systems) and don’t necessarily match.



There is no off the shelf mitigation
 Optimal responses will depend on :
   Products’ terms and conditions (e.g., preparation requirements);
   Product and channel mix (stamps, permit mail, metered mail, web
   based payments), letters vs. parcels…
   Post’s use of technology (sorting, barcoding, accounting systems) vs.
   use of manual processes.


                                                                            6
Global posts’ top concerns :
                  identification and controls, HR
                  issues, streamlining operations




Top 5 concerns
 expressed by
Posts worldwide
                                                    7
Typical leakage issues


Problems                                         Multiple root causes
  Accuracy of discounts claimed vs. postage        Overly complex (or poorly understood)
  paid (non-compliance with preparation            product terms and conditions
  requirements)

  Actual number of bulk mail items entered vs.     Fraud (on the part of mailers or postal staff)
  number on mailing statement

  Underpaid (shortpaid) mail                       Acceptance, verification and billing
                                                   processes poorly documented OR not
  Bulk mail deposited at “wrong” places (e.g.,     followed by postal staff
  collection boxes) – “bypass mail”

  Malicious duplication of e-parcels / PC          Poorly designed or executed sampling plans
  postage/meter imprints (fraud)
                                                   Lack of integration of the Post’s information
  Errors/discrepancies in                          systems (data from operations, accounting)
  reconciliation/invoicing/payment process         – islands of automation in oceans of paper
                                                   forms



                                                                                                    8
Combating revenue leakage
             A framework




Measure &    Establish
                            Combat
  Identify   Mitigation
                            Leakage
 Leakage      Policies




                                         9
Measure &                        Measuring and identifying leakage
  Identify
 Leakage                         Methodological approach


      Audit             Identify              Develop a             Sampling             Monitoring
     Existing           Critical              Sampling                 and                   &
     Systems          Dimensions               Regime               Estimation           Validation

• Leakage         • Identify critical   • Which               • Physical sampling is   • Random
  estimation is     dimensions of the     measurements?         administered             monitoring of
  not revenue       mail flow to          When? How? By                                  physical
  recovery          ensure adequate       whom?               • Engage in real time      sampling.
                    representation                              revenue leakage
• Effective                             • Conduct pilot         estimation             • Validating data
  estimation      • Develop a             studies to:                                    integrities
  precedes          targeted working    a. Generate optimal   • Update skips             ensures
  and               plan                   sample sizes         quarterly to retain      sampling occurs
  facilitates                              (Understand          optimum currency         as intended.
  recovery.                                variability);        and integrity
                                        b. Assess the
                                           constraints for
                                           sampling



                                                                                                         10
Audit

Measure &
                        Existing
                        Systems    Audit Existing Systems
  Identify
 Leakage




             Existing revenue recovery mechanisms tend to exhibit a bias to higher
             risk customers which is at odds with a simple random sampling approach
             across the entire mail flow.

             Assess the appropriateness for leakage measurement of the existing
             revenue checking system, if it does exist.
                Systems configured for revenue recovery only may not be suitable for
                measurement.


             Effective leakage measurement depends on identifying the critical
             dimensions of the mail flow.




                                                                                       11
Identify

Measure &
                        Critical
                      Dimensions     Identify the critical dimensions
  Identify
 Leakage
                                                 Defining Objectives
                                                                                Estimate Revenue Leakage Risk
                                                 Physical Sampling and
                                                  estimation process.
       How then do we identify the critical
       dimensions of the mail flow?              Segmented Sampling
                                                      Frame                         Letters                               Parcels
                                                                                                                Conceptualisation will differ
                                                                                                                slightly in content to Letters.
       A stratification process delineates the
       levels where leakages emanate from.       Adopted to ensure each      Facilities by                  Level 2 Stratification:
                                                 critical component in the   Geographical              Ensure each product segment
                                                  composition of mail is      Location                 relevant to a specific facility is
       There is a need for adequate                       captured.                                               captured.
       sampling across each of these
                                                                                    Bulk                                M1
       dimensions.                                                                 Facility               M
                                                                                                          A
                                                    Level 1 Stratification                                I
       This then provides postal                       ensures each                                       L
                                                                                                                        M2
       organizations with an estimate of            lodgement facility is        Sort Center
                                                                                                           T
                                                   captured across each
       revenue leakage at each dimension.          wide geographical unit.                                 Y
                                                                                                           P
                                                                                                           E
                                                                                                                        Mn
       In understanding revenue leakage at                                      Delivery Unit
       these sub-levels then combative
       policies may be devised to target
       problematic areas.                                                                  Time Dependant Elements
                                                 Time Dependant Elements        Cross representation of time of the day, days in the week,
                                                                                            months and quarters of the year.




                                                                                                                                             12
Develop a

Measure &
                    Sampling
                     Regime     Develop a sampling regime
  Identify
 Leakage




         Determine optimal sample sizes on a rolling basis using
             The underlying sample data
             Advanced distribution-free statistical methodologies

         Seek to estimate leakage at 95% confidence and within +/-5% precision

         Design a sampling system that is capable of dealing with the practical
         impediments of data collection, that may alter the degree of data integrity
             Tight processing windows
             Resourcing constraints
             Sample space issues.




                                                                                       13
Implement
Measure &
                       Estimation
                       Framework
                                     Implement an estimation framework
  Identify
 Leakage




    Collect, record, and transmit sample
    information to generate final estimates at a    Sample
    variety of levels
                                                                              Processing Center

    Integrated algorithms can generate final                             Letters   Flats     Parcels
    estimates at a variety of levels               Compute
                                                   Estimates                %         %         %
                                                               Stamped   Leakage   Leakage   Leakage

                                                                            %         %         %
                                                               Metered   Leakage   Leakage   Leakage
    Take action via policy responses to                                     %         %         %
                                                               Permit
    mitigate revenue leakage in a targeted                               Leakage   Leakage   Leakage
                                                    Define
    manner
                                                   Policies
         The rolling nature of the estimation
         facilitates the benchmarking of policy
         effectiveness




                                                                                                  14
Combating revenue leakage
             A framework




Measure &    Establish
                            Combat
  Identify   Mitigation
                            Leakage
 Leakage      Policies




                                         15
Establish                         Effective revenue protection policies
Mitigation
Policies                          have impacts across the board

             Customer relations
                 Impact on mailers’ mail production processes, training requirements, compliance costs
                 (new investment)
                 Changes to terms and conditions impact product convenience and demand

             Business processes
                 Impact on quality of service and personnel costs (overtime)
                 Major initiatives such as “seamless acceptance” impact work positions (e.g., for
                 verification clerks)
                 Impact on information systems (turning new data into revenue recoveries…)

             Technology solutions
                 A different response for each channel (e.g., retail vs bulk mail)
                 Measuring the ROI of proposed technology solution vs. improving/fine-tuning current
                 processes

             People and training
                 Rev Pro awareness + training on current and new processes
                 Setting KPI and monitoring compliance with processes
                 Foster cooperation between R&D, marketing, operations, and finance



                                                                                                         16
Combating revenue leakage
             A framework




Measure &    Establish
                            Combat
  Identify   Mitigation
                            Leakage
 Leakage      Policies




                                         17
Combat
                                       Discussing “acceptable” tolerance
Leakage                                levels – Royal Mail

    Background
       Royal Mail “reversions” have increased dramatically as part of its program to improve
       operational efficiencies.

          Mailers called for more “transparency” and “proportionality” (of fines) while RM insisted 100%
          compliance was needed for both revenue protection and operational purposes.

          In 2012 industry outcry prompted RM to launch industry-wide discussions .
               There is no “perfect mailing”
               What evidence should be provided by the Post’s revenue protection teams to mailers ?
               Which mail attributes should rev pro teams focus on ?


          RM has temporarily lifted specific non-compliance penalties (on sealing specs).

    Policy Implications
    Review terms and conditions and make them more explicit to increase transparency ?
    Reposition/strengthen revenue protection units on customers’ premises ?




                                                                                                           18
Combat
                             Detecting unpaid/underpaid mail: PostNL
Leakage

                         Moving from manual to
                         automated detection of
                         underpaid mail (19 CFC being
                         installed)




Automated recovery process for
single piece mail : payment
card, online payment by
recipient



Policy implications
Need to balance identification
costs with recovery costs.




                                                                       19
Combat
                                 Balancing technology and better controls :
Leakage                          SAPO (South African Post)

                                      Bulk mail is #1 priority, other
                                      streams will follow
 First mile automation: electronic
 manifesting (‘eBDN’)

 Optimized sampling plans and
 processes

 Well-trained regional revenue
 protection teams

 2 to 3 m USD recovered every
 year

Policy implications:
developing revenue protection
capability as a step-by-step
journey




                                                                         20
Combat
                             Posts in Least Developed Countries still
Leakage                      need to lay the ground work

     Carrying out revenue protection audits
         To identify/confirm main issues
         To assess robustness of current controls

     Prepare and execute revenue protection plans
         Documenting current product terms and conditions, product
         specifications, and ensuring they are met;
         Documenting processes and standards (including sampling)
         communicating on them, monitoring compliance;
         Training staff along the revenue protection along the value chain/creating teams;
         Putting in place management processes/measurement and reporting systems to ensure
         that revenue protection is managed appropriately and leakage detected;
         Longer-term, considering the RoI of low-cost technology / rev pro devices – from
         cardboard letter scales to lower-end sorters to digital meters at counters.

      Policy implications
      In LDCs streamlining current processes is a priority,
       not technology


                                                                                             21
Revenue protection moving forward :
Combat
Leakage
                            Eliminating manual verification ?
                            – U.S.P.S.
      Traditional bulk mail acceptance                Seamless acceptance
                                                          On the fly verification from scans during
                                                          processing
          Paper or electronic (e-Doc)
          documentation submitted with mailing

          Acceptance clerk samples mailing, and
          verifies documentation for accuracy

          Acceptance of statement = proof of
          mailing and payment

          Mailing is inducted after acceptance


                                                       Source : USPS (2012)
 Policy Implications
 - Building mailers’ confidence in new tracking/reporting system
 - Joint post/industry collaboration is essential (e.g., MTAC in the U.S.)
 - Automation is just part of the equation, adaptation of information systems is key + HR implications


                                                                                                      22
ERROR: stackunderflow
OFFENDING COMMAND: ~
STACK:

Weitere ähnliche Inhalte

Was ist angesagt?

Telecom Fraud Detection
Telecom Fraud DetectionTelecom Fraud Detection
Telecom Fraud DetectionPunit Kishore
 
Oracle Billing and Revenue Management(BRM)
Oracle Billing and Revenue Management(BRM)Oracle Billing and Revenue Management(BRM)
Oracle Billing and Revenue Management(BRM)Raghwendra Vikram
 
The biggest problems caused by suppliers and how to prevent them
The biggest problems caused by suppliers and how to prevent themThe biggest problems caused by suppliers and how to prevent them
The biggest problems caused by suppliers and how to prevent themAli Zeeshan
 
Reg E White Paper
Reg E White PaperReg E White Paper
Reg E White Paperpaderton
 
CIA Quebec 11 Sept 2015 Presentation C Louis Final
CIA Quebec 11 Sept 2015 Presentation C Louis FinalCIA Quebec 11 Sept 2015 Presentation C Louis Final
CIA Quebec 11 Sept 2015 Presentation C Louis FinalClaire Louis
 
PartnerTEL TEM Services
PartnerTEL TEM ServicesPartnerTEL TEM Services
PartnerTEL TEM ServicesSeanRosales
 
21 Key Questions About Optimizing Payments
21 Key Questions About Optimizing Payments21 Key Questions About Optimizing Payments
21 Key Questions About Optimizing Payments3 Point Alliance
 
Multi-supplier governance
Multi-supplier governance Multi-supplier governance
Multi-supplier governance WGroup
 
How to Evaluate a Managed Services Firm
How to Evaluate a Managed Services FirmHow to Evaluate a Managed Services Firm
How to Evaluate a Managed Services Firmoneneckitservices
 
Why rcm performance is more important than ever
Why rcm performance is more important than everWhy rcm performance is more important than ever
Why rcm performance is more important than everMaggieLewis
 
Generic VSOE Lesson
Generic VSOE LessonGeneric VSOE Lesson
Generic VSOE Lessonplamparski
 
Moving Your Contingent Workforce Program from Tactical to Strategic
Moving Your Contingent Workforce Program from Tactical to StrategicMoving Your Contingent Workforce Program from Tactical to Strategic
Moving Your Contingent Workforce Program from Tactical to StrategicPeopleFluent
 
Integrated Receivables: 5 Critical Factors For Adoption
Integrated Receivables: 5 Critical Factors For AdoptionIntegrated Receivables: 5 Critical Factors For Adoption
Integrated Receivables: 5 Critical Factors For Adoption3 Point Alliance
 
201306 Tech Decisions Webinar: Modernizing Claims for Better Customer Service
201306 Tech Decisions Webinar: Modernizing Claims for Better Customer Service201306 Tech Decisions Webinar: Modernizing Claims for Better Customer Service
201306 Tech Decisions Webinar: Modernizing Claims for Better Customer ServiceSteven Callahan
 
Free Service Desk Training Series | Service Desk First Level Resolution | Met...
Free Service Desk Training Series | Service Desk First Level Resolution | Met...Free Service Desk Training Series | Service Desk First Level Resolution | Met...
Free Service Desk Training Series | Service Desk First Level Resolution | Met...MetricNet
 
Acfe bangalore pdm 2 fraud risk - parag deodhar
Acfe bangalore pdm 2 fraud risk - parag deodharAcfe bangalore pdm 2 fraud risk - parag deodhar
Acfe bangalore pdm 2 fraud risk - parag deodharParag Deodhar
 
Management model for exploratory investment in IT
Management model for exploratory investment in IT Management model for exploratory investment in IT
Management model for exploratory investment in IT WGroup
 
Survey Costing
Survey CostingSurvey Costing
Survey Costingkarlfeld
 

Was ist angesagt? (20)

Telecom Fraud Detection
Telecom Fraud DetectionTelecom Fraud Detection
Telecom Fraud Detection
 
Oracle Billing and Revenue Management(BRM)
Oracle Billing and Revenue Management(BRM)Oracle Billing and Revenue Management(BRM)
Oracle Billing and Revenue Management(BRM)
 
The Next Generation of Submission Intake and Clearance
The Next Generation of Submission Intake and ClearanceThe Next Generation of Submission Intake and Clearance
The Next Generation of Submission Intake and Clearance
 
Top 8 Ways to Improve Underwriting Workflow
Top 8 Ways to Improve Underwriting WorkflowTop 8 Ways to Improve Underwriting Workflow
Top 8 Ways to Improve Underwriting Workflow
 
The biggest problems caused by suppliers and how to prevent them
The biggest problems caused by suppliers and how to prevent themThe biggest problems caused by suppliers and how to prevent them
The biggest problems caused by suppliers and how to prevent them
 
Reg E White Paper
Reg E White PaperReg E White Paper
Reg E White Paper
 
CIA Quebec 11 Sept 2015 Presentation C Louis Final
CIA Quebec 11 Sept 2015 Presentation C Louis FinalCIA Quebec 11 Sept 2015 Presentation C Louis Final
CIA Quebec 11 Sept 2015 Presentation C Louis Final
 
PartnerTEL TEM Services
PartnerTEL TEM ServicesPartnerTEL TEM Services
PartnerTEL TEM Services
 
21 Key Questions About Optimizing Payments
21 Key Questions About Optimizing Payments21 Key Questions About Optimizing Payments
21 Key Questions About Optimizing Payments
 
Multi-supplier governance
Multi-supplier governance Multi-supplier governance
Multi-supplier governance
 
How to Evaluate a Managed Services Firm
How to Evaluate a Managed Services FirmHow to Evaluate a Managed Services Firm
How to Evaluate a Managed Services Firm
 
Why rcm performance is more important than ever
Why rcm performance is more important than everWhy rcm performance is more important than ever
Why rcm performance is more important than ever
 
Generic VSOE Lesson
Generic VSOE LessonGeneric VSOE Lesson
Generic VSOE Lesson
 
Moving Your Contingent Workforce Program from Tactical to Strategic
Moving Your Contingent Workforce Program from Tactical to StrategicMoving Your Contingent Workforce Program from Tactical to Strategic
Moving Your Contingent Workforce Program from Tactical to Strategic
 
Integrated Receivables: 5 Critical Factors For Adoption
Integrated Receivables: 5 Critical Factors For AdoptionIntegrated Receivables: 5 Critical Factors For Adoption
Integrated Receivables: 5 Critical Factors For Adoption
 
201306 Tech Decisions Webinar: Modernizing Claims for Better Customer Service
201306 Tech Decisions Webinar: Modernizing Claims for Better Customer Service201306 Tech Decisions Webinar: Modernizing Claims for Better Customer Service
201306 Tech Decisions Webinar: Modernizing Claims for Better Customer Service
 
Free Service Desk Training Series | Service Desk First Level Resolution | Met...
Free Service Desk Training Series | Service Desk First Level Resolution | Met...Free Service Desk Training Series | Service Desk First Level Resolution | Met...
Free Service Desk Training Series | Service Desk First Level Resolution | Met...
 
Acfe bangalore pdm 2 fraud risk - parag deodhar
Acfe bangalore pdm 2 fraud risk - parag deodharAcfe bangalore pdm 2 fraud risk - parag deodhar
Acfe bangalore pdm 2 fraud risk - parag deodhar
 
Management model for exploratory investment in IT
Management model for exploratory investment in IT Management model for exploratory investment in IT
Management model for exploratory investment in IT
 
Survey Costing
Survey CostingSurvey Costing
Survey Costing
 

Andere mochten auch

Revenue Assurance Industry Update - Webinar by Dr. Gadi Solotorevsky, cVidya'...
Revenue Assurance Industry Update - Webinar by Dr. Gadi Solotorevsky, cVidya'...Revenue Assurance Industry Update - Webinar by Dr. Gadi Solotorevsky, cVidya'...
Revenue Assurance Industry Update - Webinar by Dr. Gadi Solotorevsky, cVidya'...cVidya Networks
 
Zen Infographic - Revenue Assurance Automation
Zen Infographic - Revenue Assurance AutomationZen Infographic - Revenue Assurance Automation
Zen Infographic - Revenue Assurance AutomationSubex
 
Tech M White Paper Revenue Assurance D0 9 180612 (1)
Tech M White Paper Revenue Assurance D0 9 180612 (1)Tech M White Paper Revenue Assurance D0 9 180612 (1)
Tech M White Paper Revenue Assurance D0 9 180612 (1)aprasoon
 
Revenue Assurance, Fraud Reduction and Cost Managment in Telecoms Conference
Revenue Assurance, Fraud Reduction and Cost Managment in Telecoms ConferenceRevenue Assurance, Fraud Reduction and Cost Managment in Telecoms Conference
Revenue Assurance, Fraud Reduction and Cost Managment in Telecoms ConferenceArena International
 
"The Impact of Data Traffic Explosion and LTE on Revenue Assurance and Risk"
 "The Impact of Data Traffic Explosion and LTE on Revenue Assurance and Risk"  "The Impact of Data Traffic Explosion and LTE on Revenue Assurance and Risk"
"The Impact of Data Traffic Explosion and LTE on Revenue Assurance and Risk" cVidya Networks
 
Preventing Revenue Leakage and Monitoring Distributed Systems with Machine Le...
Preventing Revenue Leakage and Monitoring Distributed Systems with Machine Le...Preventing Revenue Leakage and Monitoring Distributed Systems with Machine Le...
Preventing Revenue Leakage and Monitoring Distributed Systems with Machine Le...Spark Summit
 
How to Leverage Big Data to Help Finding Fraud Patterns & Revenue Assurance
How to Leverage Big Data to Help Finding Fraud Patterns & Revenue AssuranceHow to Leverage Big Data to Help Finding Fraud Patterns & Revenue Assurance
How to Leverage Big Data to Help Finding Fraud Patterns & Revenue AssurancecVidya Networks
 
Revenue assurance in telecom
Revenue assurance in telecomRevenue assurance in telecom
Revenue assurance in telecomcVidya Networks
 

Andere mochten auch (9)

Revenue Assurance Industry Update - Webinar by Dr. Gadi Solotorevsky, cVidya'...
Revenue Assurance Industry Update - Webinar by Dr. Gadi Solotorevsky, cVidya'...Revenue Assurance Industry Update - Webinar by Dr. Gadi Solotorevsky, cVidya'...
Revenue Assurance Industry Update - Webinar by Dr. Gadi Solotorevsky, cVidya'...
 
Zen Infographic - Revenue Assurance Automation
Zen Infographic - Revenue Assurance AutomationZen Infographic - Revenue Assurance Automation
Zen Infographic - Revenue Assurance Automation
 
Tech M White Paper Revenue Assurance D0 9 180612 (1)
Tech M White Paper Revenue Assurance D0 9 180612 (1)Tech M White Paper Revenue Assurance D0 9 180612 (1)
Tech M White Paper Revenue Assurance D0 9 180612 (1)
 
Revenue Assurance, Fraud Reduction and Cost Managment in Telecoms Conference
Revenue Assurance, Fraud Reduction and Cost Managment in Telecoms ConferenceRevenue Assurance, Fraud Reduction and Cost Managment in Telecoms Conference
Revenue Assurance, Fraud Reduction and Cost Managment in Telecoms Conference
 
"The Impact of Data Traffic Explosion and LTE on Revenue Assurance and Risk"
 "The Impact of Data Traffic Explosion and LTE on Revenue Assurance and Risk"  "The Impact of Data Traffic Explosion and LTE on Revenue Assurance and Risk"
"The Impact of Data Traffic Explosion and LTE on Revenue Assurance and Risk"
 
Preventing Revenue Leakage and Monitoring Distributed Systems with Machine Le...
Preventing Revenue Leakage and Monitoring Distributed Systems with Machine Le...Preventing Revenue Leakage and Monitoring Distributed Systems with Machine Le...
Preventing Revenue Leakage and Monitoring Distributed Systems with Machine Le...
 
The future of r av3
The future of r av3The future of r av3
The future of r av3
 
How to Leverage Big Data to Help Finding Fraud Patterns & Revenue Assurance
How to Leverage Big Data to Help Finding Fraud Patterns & Revenue AssuranceHow to Leverage Big Data to Help Finding Fraud Patterns & Revenue Assurance
How to Leverage Big Data to Help Finding Fraud Patterns & Revenue Assurance
 
Revenue assurance in telecom
Revenue assurance in telecomRevenue assurance in telecom
Revenue assurance in telecom
 

Ähnlich wie Combat Revenue Leakage

2013 03 18 webinar 2013 combating revenue leakage
2013 03 18 webinar 2013   combating revenue leakage2013 03 18 webinar 2013   combating revenue leakage
2013 03 18 webinar 2013 combating revenue leakagedecision/analysis partners
 
Rutgers Research Center
Rutgers Research CenterRutgers Research Center
Rutgers Research Centercarlabrut
 
The Coming Age of Continuous Auditing
The Coming Age of Continuous AuditingThe Coming Age of Continuous Auditing
The Coming Age of Continuous Auditingcarlabrut
 
Sym Sure Revenue Assurance
Sym Sure Revenue AssuranceSym Sure Revenue Assurance
Sym Sure Revenue Assurancejjfrec07
 
Metrics, Risk Management & DLP
Metrics, Risk Management & DLPMetrics, Risk Management & DLP
Metrics, Risk Management & DLPRobert Kloots
 
Knowledge Management Maturity Models and Phased Measurement
Knowledge Management Maturity Models and Phased MeasurementKnowledge Management Maturity Models and Phased Measurement
Knowledge Management Maturity Models and Phased MeasurementPatrick Murphy
 
An Introduction to ORYX Software
An Introduction to ORYX SoftwareAn Introduction to ORYX Software
An Introduction to ORYX SoftwareAccountagility
 
Risk Mitigation Trees - Review test handovers with stakeholders (2004)
Risk Mitigation Trees - Review test handovers with stakeholders (2004)Risk Mitigation Trees - Review test handovers with stakeholders (2004)
Risk Mitigation Trees - Review test handovers with stakeholders (2004)Neil Thompson
 
Operational Risk : Take a look at the raw canvas
Operational Risk : Take a look at the raw canvasOperational Risk : Take a look at the raw canvas
Operational Risk : Take a look at the raw canvasTreat Risk
 
Lean Distribution
Lean DistributionLean Distribution
Lean DistributionAL Systems
 
Tim Bates Mba Technology Conference 2007 Data Mining Presentation
Tim Bates Mba Technology Conference 2007 Data Mining PresentationTim Bates Mba Technology Conference 2007 Data Mining Presentation
Tim Bates Mba Technology Conference 2007 Data Mining Presentationtimbates2
 
Sym Sure Loan Portfolio
Sym Sure Loan PortfolioSym Sure Loan Portfolio
Sym Sure Loan Portfoliojjfrec07
 
Brainstorming failure
Brainstorming failureBrainstorming failure
Brainstorming failureJeffery Smith
 
The Era of Evidence-Based Business Process Management by Marlon Dumas
The Era of Evidence-Based Business Process Management by Marlon DumasThe Era of Evidence-Based Business Process Management by Marlon Dumas
The Era of Evidence-Based Business Process Management by Marlon DumasLEADingPractice
 
Mazars Model Audit Methodology
Mazars Model Audit MethodologyMazars Model Audit Methodology
Mazars Model Audit MethodologyJerome Brice
 
Exploring Relationship Between Risk & Compliance
Exploring Relationship Between Risk & ComplianceExploring Relationship Between Risk & Compliance
Exploring Relationship Between Risk & ComplianceComplianceTrack
 
threat_and_vulnerability_management_-_ryan_elmer_-_frsecure.pptx
threat_and_vulnerability_management_-_ryan_elmer_-_frsecure.pptxthreat_and_vulnerability_management_-_ryan_elmer_-_frsecure.pptx
threat_and_vulnerability_management_-_ryan_elmer_-_frsecure.pptxImXaib
 

Ähnlich wie Combat Revenue Leakage (20)

2013 03 18 webinar 2013 combating revenue leakage
2013 03 18 webinar 2013   combating revenue leakage2013 03 18 webinar 2013   combating revenue leakage
2013 03 18 webinar 2013 combating revenue leakage
 
Rutgers Research Center
Rutgers Research CenterRutgers Research Center
Rutgers Research Center
 
The Coming Age of Continuous Auditing
The Coming Age of Continuous AuditingThe Coming Age of Continuous Auditing
The Coming Age of Continuous Auditing
 
Audit Sampling
Audit SamplingAudit Sampling
Audit Sampling
 
Sym Sure Revenue Assurance
Sym Sure Revenue AssuranceSym Sure Revenue Assurance
Sym Sure Revenue Assurance
 
Metrics, Risk Management & DLP
Metrics, Risk Management & DLPMetrics, Risk Management & DLP
Metrics, Risk Management & DLP
 
Q insure
Q insure Q insure
Q insure
 
Knowledge Management Maturity Models and Phased Measurement
Knowledge Management Maturity Models and Phased MeasurementKnowledge Management Maturity Models and Phased Measurement
Knowledge Management Maturity Models and Phased Measurement
 
An Introduction to ORYX Software
An Introduction to ORYX SoftwareAn Introduction to ORYX Software
An Introduction to ORYX Software
 
Risk Mitigation Trees - Review test handovers with stakeholders (2004)
Risk Mitigation Trees - Review test handovers with stakeholders (2004)Risk Mitigation Trees - Review test handovers with stakeholders (2004)
Risk Mitigation Trees - Review test handovers with stakeholders (2004)
 
Operational Risk : Take a look at the raw canvas
Operational Risk : Take a look at the raw canvasOperational Risk : Take a look at the raw canvas
Operational Risk : Take a look at the raw canvas
 
Lean Distribution
Lean DistributionLean Distribution
Lean Distribution
 
Tim Bates Mba Technology Conference 2007 Data Mining Presentation
Tim Bates Mba Technology Conference 2007 Data Mining PresentationTim Bates Mba Technology Conference 2007 Data Mining Presentation
Tim Bates Mba Technology Conference 2007 Data Mining Presentation
 
Sym Sure Loan Portfolio
Sym Sure Loan PortfolioSym Sure Loan Portfolio
Sym Sure Loan Portfolio
 
Brainstorming failure
Brainstorming failureBrainstorming failure
Brainstorming failure
 
The Era of Evidence-Based Business Process Management by Marlon Dumas
The Era of Evidence-Based Business Process Management by Marlon DumasThe Era of Evidence-Based Business Process Management by Marlon Dumas
The Era of Evidence-Based Business Process Management by Marlon Dumas
 
Utility bill
Utility billUtility bill
Utility bill
 
Mazars Model Audit Methodology
Mazars Model Audit MethodologyMazars Model Audit Methodology
Mazars Model Audit Methodology
 
Exploring Relationship Between Risk & Compliance
Exploring Relationship Between Risk & ComplianceExploring Relationship Between Risk & Compliance
Exploring Relationship Between Risk & Compliance
 
threat_and_vulnerability_management_-_ryan_elmer_-_frsecure.pptx
threat_and_vulnerability_management_-_ryan_elmer_-_frsecure.pptxthreat_and_vulnerability_management_-_ryan_elmer_-_frsecure.pptx
threat_and_vulnerability_management_-_ryan_elmer_-_frsecure.pptx
 

Mehr von decision/analysis partners LLC

Mehr von decision/analysis partners LLC (19)

Postal Performance Measurement slideshare
Postal Performance Measurement slidesharePostal Performance Measurement slideshare
Postal Performance Measurement slideshare
 
Webinar 2013 delivery sequencing webinar
Webinar 2013   delivery sequencing webinarWebinar 2013   delivery sequencing webinar
Webinar 2013 delivery sequencing webinar
 
Plateforme et Solutions : Le Futur de la Poste
Plateforme et Solutions : Le Futur de la PostePlateforme et Solutions : Le Futur de la Poste
Plateforme et Solutions : Le Futur de la Poste
 
2012 02 mer developing postal platforms
2012 02 mer developing postal platforms2012 02 mer developing postal platforms
2012 02 mer developing postal platforms
 
The Adaptable Post
The Adaptable PostThe Adaptable Post
The Adaptable Post
 
Case study ghana postal policy
Case study   ghana postal policyCase study   ghana postal policy
Case study ghana postal policy
 
Capability operations management
Capability   operations managementCapability   operations management
Capability operations management
 
Case study network simulation for oig
Case study   network simulation for oigCase study   network simulation for oig
Case study network simulation for oig
 
Case study redesigning the montreal lpp
Case study   redesigning the montreal lppCase study   redesigning the montreal lpp
Case study redesigning the montreal lpp
 
Capability modeling
Capability   modelingCapability   modeling
Capability modeling
 
Capability plant and work center design
Capability   plant and work center designCapability   plant and work center design
Capability plant and work center design
 
Case study canada post transformation
Case study   canada post transformationCase study   canada post transformation
Case study canada post transformation
 
Capability network management
Capability   network managementCapability   network management
Capability network management
 
The Adaptable Post
The Adaptable PostThe Adaptable Post
The Adaptable Post
 
Capability labor planning scheduling
Capability   labor planning  schedulingCapability   labor planning  scheduling
Capability labor planning scheduling
 
Capability delivery management v2
Capability   delivery management v2Capability   delivery management v2
Capability delivery management v2
 
Capabilities postal industry
Capabilities   postal industryCapabilities   postal industry
Capabilities postal industry
 
Business intelligence for the postal operator
Business intelligence for the postal operatorBusiness intelligence for the postal operator
Business intelligence for the postal operator
 
Address systems and the future of the mail
Address systems and the future of the mailAddress systems and the future of the mail
Address systems and the future of the mail
 

Combat Revenue Leakage

  • 1. Combating Revenue Leakage Prepared by With the Assistance of Chris Paterson JP Ducasse
  • 2. Webinar Outline Leakage – definition and overview Overview of a general framework to combat leakage Measuring leakage Establishing mitigation policies Combating leakage What you should consider 2
  • 3. Combating revenue leakage Definition* Combating revenue leakage consists of engaging in activities that help a Post: Collect all the postage revenue owed to it, and Curb the sources/reasons of leakage. Leakage stems from one of four main risks Counterfeit (e.g., illegal issues, fake imprints) Bypass mail (e.g., mail inducted without any form of payment) Shortpaid or underpaid (e.g., mail tendered with insufficient postage) Problems related to billing or postage collection (e.g., bad cheques; accounting errors) Combating revenue leakage consists of setting policies to mitigate the sources of risks * Source: UPU Consultative Committee – Postal Revenue Protection Working Group 3
  • 4. Recent trends Steps in the right direction But room for improvement • Global awareness of leakage • Not all posts have established a well- issues has increased (75% of posts structured revenue protection function admit they experience leakage) • Posts have heavily invested in • Mail acceptance and verification is still revenue protection technology, very much manual and time consuming, making some channels more and often plagued with inconsistencies in secure (meters, stamps) performance. • Verification technologies (e.g., • Fraudsters too leverage technologies... OCR-based) becoming more • New products may not be ‘leakage-free’ effective and/or more affordable • ROI of technology solutions is still an and scalable issue, e.g., for smaller posts 4
  • 5. A broader choice of technologies is now available to fight leakage Evidencing • Deployment of digital meters in smaller emerging markets • Anti-fraud security measures (special inks, holograms…) for stamps Acceptance/verification • E-documentation • Sorters/counting machines for piece count (for sampling, verification or terminal dues purposes) • Modular dimensions/weight/data capture solutions for use in post offices A few examples Processing • Lower-end sorters suitable for mid-tier posts • Large CFC with on the fly weighing of parcels or letters • Capability to trace back an item to a specific sender Billing/reconciling software solutions (e.g., USPS Permit RP project) 5
  • 6. Two main challenges Measuring and identification is difficult A touchy issue : leakages relate to posts’ weaknesses - a mix of fraud and (operational or accounting) issues; Amounts recovered are just the tip of the iceberg; Posts use multiple channels and processes; Data sources are diverse (spot checks, sampling, data from operations and from accounting systems) and don’t necessarily match. There is no off the shelf mitigation Optimal responses will depend on : Products’ terms and conditions (e.g., preparation requirements); Product and channel mix (stamps, permit mail, metered mail, web based payments), letters vs. parcels… Post’s use of technology (sorting, barcoding, accounting systems) vs. use of manual processes. 6
  • 7. Global posts’ top concerns : identification and controls, HR issues, streamlining operations Top 5 concerns expressed by Posts worldwide 7
  • 8. Typical leakage issues Problems Multiple root causes Accuracy of discounts claimed vs. postage Overly complex (or poorly understood) paid (non-compliance with preparation product terms and conditions requirements) Actual number of bulk mail items entered vs. Fraud (on the part of mailers or postal staff) number on mailing statement Underpaid (shortpaid) mail Acceptance, verification and billing processes poorly documented OR not Bulk mail deposited at “wrong” places (e.g., followed by postal staff collection boxes) – “bypass mail” Malicious duplication of e-parcels / PC Poorly designed or executed sampling plans postage/meter imprints (fraud) Lack of integration of the Post’s information Errors/discrepancies in systems (data from operations, accounting) reconciliation/invoicing/payment process – islands of automation in oceans of paper forms 8
  • 9. Combating revenue leakage A framework Measure & Establish Combat Identify Mitigation Leakage Leakage Policies 9
  • 10. Measure & Measuring and identifying leakage Identify Leakage Methodological approach Audit Identify Develop a Sampling Monitoring Existing Critical Sampling and & Systems Dimensions Regime Estimation Validation • Leakage • Identify critical • Which • Physical sampling is • Random estimation is dimensions of the measurements? administered monitoring of not revenue mail flow to When? How? By physical recovery ensure adequate whom? • Engage in real time sampling. representation revenue leakage • Effective • Conduct pilot estimation • Validating data estimation • Develop a studies to: integrities precedes targeted working a. Generate optimal • Update skips ensures and plan sample sizes quarterly to retain sampling occurs facilitates (Understand optimum currency as intended. recovery. variability); and integrity b. Assess the constraints for sampling 10
  • 11. Audit Measure & Existing Systems Audit Existing Systems Identify Leakage Existing revenue recovery mechanisms tend to exhibit a bias to higher risk customers which is at odds with a simple random sampling approach across the entire mail flow. Assess the appropriateness for leakage measurement of the existing revenue checking system, if it does exist. Systems configured for revenue recovery only may not be suitable for measurement. Effective leakage measurement depends on identifying the critical dimensions of the mail flow. 11
  • 12. Identify Measure & Critical Dimensions Identify the critical dimensions Identify Leakage Defining Objectives Estimate Revenue Leakage Risk Physical Sampling and estimation process. How then do we identify the critical dimensions of the mail flow? Segmented Sampling Frame Letters Parcels Conceptualisation will differ slightly in content to Letters. A stratification process delineates the levels where leakages emanate from. Adopted to ensure each Facilities by Level 2 Stratification: critical component in the Geographical Ensure each product segment composition of mail is Location relevant to a specific facility is There is a need for adequate captured. captured. sampling across each of these Bulk M1 dimensions. Facility M A Level 1 Stratification I This then provides postal ensures each L M2 organizations with an estimate of lodgement facility is Sort Center T captured across each revenue leakage at each dimension. wide geographical unit. Y P E Mn In understanding revenue leakage at Delivery Unit these sub-levels then combative policies may be devised to target problematic areas. Time Dependant Elements Time Dependant Elements Cross representation of time of the day, days in the week, months and quarters of the year. 12
  • 13. Develop a Measure & Sampling Regime Develop a sampling regime Identify Leakage Determine optimal sample sizes on a rolling basis using The underlying sample data Advanced distribution-free statistical methodologies Seek to estimate leakage at 95% confidence and within +/-5% precision Design a sampling system that is capable of dealing with the practical impediments of data collection, that may alter the degree of data integrity Tight processing windows Resourcing constraints Sample space issues. 13
  • 14. Implement Measure & Estimation Framework Implement an estimation framework Identify Leakage Collect, record, and transmit sample information to generate final estimates at a Sample variety of levels Processing Center Integrated algorithms can generate final Letters Flats Parcels estimates at a variety of levels Compute Estimates % % % Stamped Leakage Leakage Leakage % % % Metered Leakage Leakage Leakage Take action via policy responses to % % % Permit mitigate revenue leakage in a targeted Leakage Leakage Leakage Define manner Policies The rolling nature of the estimation facilitates the benchmarking of policy effectiveness 14
  • 15. Combating revenue leakage A framework Measure & Establish Combat Identify Mitigation Leakage Leakage Policies 15
  • 16. Establish Effective revenue protection policies Mitigation Policies have impacts across the board Customer relations Impact on mailers’ mail production processes, training requirements, compliance costs (new investment) Changes to terms and conditions impact product convenience and demand Business processes Impact on quality of service and personnel costs (overtime) Major initiatives such as “seamless acceptance” impact work positions (e.g., for verification clerks) Impact on information systems (turning new data into revenue recoveries…) Technology solutions A different response for each channel (e.g., retail vs bulk mail) Measuring the ROI of proposed technology solution vs. improving/fine-tuning current processes People and training Rev Pro awareness + training on current and new processes Setting KPI and monitoring compliance with processes Foster cooperation between R&D, marketing, operations, and finance 16
  • 17. Combating revenue leakage A framework Measure & Establish Combat Identify Mitigation Leakage Leakage Policies 17
  • 18. Combat Discussing “acceptable” tolerance Leakage levels – Royal Mail Background Royal Mail “reversions” have increased dramatically as part of its program to improve operational efficiencies. Mailers called for more “transparency” and “proportionality” (of fines) while RM insisted 100% compliance was needed for both revenue protection and operational purposes. In 2012 industry outcry prompted RM to launch industry-wide discussions . There is no “perfect mailing” What evidence should be provided by the Post’s revenue protection teams to mailers ? Which mail attributes should rev pro teams focus on ? RM has temporarily lifted specific non-compliance penalties (on sealing specs). Policy Implications Review terms and conditions and make them more explicit to increase transparency ? Reposition/strengthen revenue protection units on customers’ premises ? 18
  • 19. Combat Detecting unpaid/underpaid mail: PostNL Leakage Moving from manual to automated detection of underpaid mail (19 CFC being installed) Automated recovery process for single piece mail : payment card, online payment by recipient Policy implications Need to balance identification costs with recovery costs. 19
  • 20. Combat Balancing technology and better controls : Leakage SAPO (South African Post) Bulk mail is #1 priority, other streams will follow First mile automation: electronic manifesting (‘eBDN’) Optimized sampling plans and processes Well-trained regional revenue protection teams 2 to 3 m USD recovered every year Policy implications: developing revenue protection capability as a step-by-step journey 20
  • 21. Combat Posts in Least Developed Countries still Leakage need to lay the ground work Carrying out revenue protection audits To identify/confirm main issues To assess robustness of current controls Prepare and execute revenue protection plans Documenting current product terms and conditions, product specifications, and ensuring they are met; Documenting processes and standards (including sampling) communicating on them, monitoring compliance; Training staff along the revenue protection along the value chain/creating teams; Putting in place management processes/measurement and reporting systems to ensure that revenue protection is managed appropriately and leakage detected; Longer-term, considering the RoI of low-cost technology / rev pro devices – from cardboard letter scales to lower-end sorters to digital meters at counters. Policy implications In LDCs streamlining current processes is a priority, not technology 21
  • 22. Revenue protection moving forward : Combat Leakage Eliminating manual verification ? – U.S.P.S. Traditional bulk mail acceptance Seamless acceptance On the fly verification from scans during processing Paper or electronic (e-Doc) documentation submitted with mailing Acceptance clerk samples mailing, and verifies documentation for accuracy Acceptance of statement = proof of mailing and payment Mailing is inducted after acceptance Source : USPS (2012) Policy Implications - Building mailers’ confidence in new tracking/reporting system - Joint post/industry collaboration is essential (e.g., MTAC in the U.S.) - Automation is just part of the equation, adaptation of information systems is key + HR implications 22
  • 23.